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The Ubicomp Digital 2020 -- Time Series Classification Challenge from STABILOis a challenge about multi-variate time series classification. The datacollected from 100 volunteer writers, and contains 15 features measured withmultiple sensors on a pen. In this paper,we use a neural network to classifythe data into 52 classes, that is lower and upper cases of Arabic letters. Theproposed architecture of the neural network a is CNN-LSTM network. It combinesconvolutional neural network (CNN) for short term context with along short termmemory layer (LSTM) for also long term dependencies. We reached an accuracy of68% on our writer exclusive test set and64.6% on the blind challenge test setresulting in the second place.

Ubicomp Digital 2020 -- Handwriting classification using a convolutional recurrent network